AI Medical Compendium Topic

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Position-Aware Participation-Contributed Temporal Dynamic Model for Group Activity Recognition.

IEEE transactions on neural networks and learning systems
Group activity recognition (GAR) aiming at understanding the behavior of a group of people in a video clip has received increasing attention recently. Nevertheless, most of the existing solutions ignore that not all the persons contribute to the grou...

A Survey of Modulation Classification Using Deep Learning: Signal Representation and Data Preprocessing.

IEEE transactions on neural networks and learning systems
Modulation classification is one of the key tasks for communications systems monitoring, management, and control for addressing technical issues, including spectrum awareness, adaptive transmissions, and interference avoidance. Recently, deep learnin...

Cardiovascular magnetic resonance images with susceptibility artifacts: artificial intelligence with spatial-attention for ventricular volumes and mass assessment.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Segmentation of cardiovascular magnetic resonance (CMR) images is an essential step for evaluating dimensional and functional ventricular parameters as ejection fraction (EF) but may be limited by artifacts, which represent the major chal...

Deep Temporal Model-Based Identity-Aware Hand Detection for Space Human-Robot Interaction.

IEEE transactions on cybernetics
Hand detection is a crucial technology for space human-robot interaction (SHRI), and the awareness of hand identities is particularly critical. However, most advanced works have three limitations: 1) the low detection accuracy of small-size objects; ...

Continual learning with attentive recurrent neural networks for temporal data classification.

Neural networks : the official journal of the International Neural Network Society
Continual learning is an emerging research branch of deep learning, which aims to learn a model for a series of tasks continually without forgetting knowledge obtained from previous tasks. Despite receiving a lot of attention in the research communit...

Data-Driven Guided Attention for Analysis of Physiological Waveforms With Deep Learning.

IEEE journal of biomedical and health informatics
Estimating physiological parameters - such as blood pressure (BP) - from raw sensor data captured by noninvasive, wearable devices rely on either burdensome manual feature extraction designed by domain experts to identify key waveform characteristics...

3DCANN: A Spatio-Temporal Convolution Attention Neural Network for EEG Emotion Recognition.

IEEE journal of biomedical and health informatics
Since electroencephalogram (EEG) signals can truly reflect human emotional state, emotion recognition based on EEG has turned into a critical branch in the field of artificial intelligence. Aiming at the disparity of EEG signals in various emotional ...

Multiple instance neural networks based on sparse attention for cancer detection using T-cell receptor sequences.

BMC bioinformatics
Early detection of cancers has been much explored due to its paramount importance in biomedical fields. Among different types of data used to answer this biological question, studies based on T cell receptors (TCRs) are under recent spotlight due to ...

Feature Pyramid U-Net with Attention for Semantic Segmentation of Forward-Looking Sonar Images.

Sensors (Basel, Switzerland)
Forward-looking sonar is a technique widely used for underwater detection. However, most sonar images have underwater noise and low resolution due to their acoustic properties. In recent years, the semantic segmentation model U-Net has shown excellen...

Biomedical named entity recognition with the combined feature attention and fully-shared multi-task learning.

BMC bioinformatics
BACKGROUND: Biomedical named entity recognition (BioNER) is a basic and important task for biomedical text mining with the purpose of automatically recognizing and classifying biomedical entities. The performance of BioNER systems directly impacts do...